CN110008602A - Take the road network choosing method of multiple features coordination under a kind of large scale into account - Google Patents
Take the road network choosing method of multiple features coordination under a kind of large scale into account Download PDFInfo
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Abstract
The invention discloses the road network choosing methods for taking multiple features coordination under a kind of large scale into account, including construct point, segmental arc, Polygon Topology for road network, identify mesh therein；Consider that semantic road, geometry and topological characteristic generate stroke connection simultaneously, and identifies tip segmental arc and tip mesh；Determine reticular density threshold value and road stroke connection importance threshold value；According to tip segmental arc and tip mesh, road stroke type is divided；And etc..Advantage is: by using the road network choosing method, can take path connected, integrality and road network network characterization into account during road network is chosen and local density's multiple features are coordinated to complete road network selection；When carrying out the selection of large scale road, the spatial character of road network can be preferably kept；When carrying out the selection of large scale road, the connectivity and integrality of road network can be preferably kept, and while taking road network connectivity into account, summarise the road network structure of road well.
Description
Technical field
The present invention relates to the roads for taking multiple features coordination under geographic mapping technical field more particularly to a kind of large scale into account
Net choosing method.
Background technique
Road network on map is the objective building to the true geographical world's road network connection and distribution situation, is map
Skeleton element.In general, road network level is various, relationship is complicated, at network-like, therefore, road network automatic Synthesis is always one
A difficulties.During road network is chosen, the emphasis of selection depends on scale bar span, however, existing research does not limit
The applicable synthesis scale bar range of its method, for the Automated Map Generalization of Large-scale Urban (being greater than 1:100000) road network
For, it is very fine to the building of road network, therefore, during carrying out automatic Synthesis selection to it, it should consider road certainly
Connectivity, the integrality of body take the network characteristic and density feature of road network entirety into account again.
It includes two aspects that road network, which chooses process: choosing how many and which is chosen, when scale bar changes, choose
As a result spatial distribution characteristic places one's entire reliance upon the two elements.Wherein, the former is quota On The Choice, can generally pass through root
Model solves；The latter is structuring, optimizes On The Choice, is had been a hot spot of research.In existing research, based on graph theory
Choosing method be tissue road net data, take into account road network topology constraint lay a good foundation, however, this method is difficult to realize road network
Structured selection.Existing road network choosing method has: the first, pass through the good continuity being introduced into Gestalt visual perception
Section is connected into stroke as object is chosen, completes choosing according to stroke importance by (good continuation) principle
It takes, to guarantee the connectivity of road network；Second, stroke importance is calculated, stroke importance is evaluated with length index, but should
Evaluation index is excessively single；The third, considers the length, degree of communication and the averag density comprising segmental arc of stroke, is added
Connected degree, centrad and category of roads of the stroke in road network, type other semantic informations, second and the third side
Method can effectively simulate the road vision length in artificial choose, and keep considering road target entirety while path connected
Property, i.e., it can identify that primary and secondary wants road, however, causing its to choose result road the selection aspect relative coarseness of secondary road
Net network characterization and road network local density Character losing；4th kind, partial zones are reflected with the reticular density in road data
The road concentration in domain, and obtain density threshold, determines selection rate, this method maintain well road network in density, open up
It flutters, the feature in terms of geometry and semanteme, but because it is made trade-offs as unit of section, often gives up intermediate section, destroy road network
Connectivity.
Summary of the invention
The purpose of the present invention is to provide the road network choosing methods for taking multiple features coordination under a kind of large scale into account, to solve
Foregoing problems certainly existing in the prior art.
To achieve the goals above, The technical solution adopted by the invention is as follows:
The road network choosing method for taking multiple features coordination under a kind of large scale into account, includes the following steps,
S1, point, segmental arc, Polygon Topology are constructed for road network, identifies mesh therein；Road semanteme, geometry are considered simultaneously
And topological characteristic generates stroke connection, and identifies tip segmental arc and tip mesh；
S2, reticular density threshold value and road stroke connection importance threshold value are determined；
S3, according to tip segmental arc and tip mesh, divide road stroke type；
S4, judge whether each stroke connection in ready-portioned road stroke type is containing tip mesh
Stroke connection, if it is not, thening follow the steps S5；If so, thening follow the steps S7.
S5, according to road stroke type, calculate the importance of road stroke connection；
S6, judge whether the importance of road stroke connection is less than stroke connection importance threshold value, if so, deleting
Road stroke connection, if it is not, then retaining road stroke connection；
S7, it the stroke connection containing tip mesh is collected obtains tip mesh set；
S8, classified according to the type containing road stroke in mesh to tip mesh set, handle the big of identification
In the tip mesh of reticular density threshold value, the maximum tip mesh of density and associated road stroke set are separated, and
Compare road stroke importance, obtains the smallest road stroke of importance；
S9, the smallest road stroke of importance is deleted；And judge whether that suspension segmental arc can be generated, if not generating suspension arc
Section, then delete road stroke, and merge the topological Polygon of road stroke the right and left, generate new mesh；If
Suspension segmental arc is generated, then deletes the tip section of road stroke in tip mesh, merges the topology of the section the right and left
Polygon generates new mesh；
S10, judge whether currently processed tip mesh is that the last one in tip mesh set is greater than reticular density threshold
The tip mesh of value, if so, the mesh that output is new, if it is not, then return step S8.
Preferably, the identification process of tip segmental arc is in step S1, identify road stroke connection in the road
Segmental arc of the intersection number less than 2 of all segmental arcs in stroke connection, the segmental arc are referred to as the tip in road stroke connection
Segmental arc；Identify that, there are the identical closure segmental arc of head and the tail node, which also belongs to tip segmental arc simultaneously.
Preferably, the identification process of tip mesh is in step S1, according to road network topology relationship, identifies network meshes, will
Mesh containing tip segmental arc in road stroke connection is known as tip mesh.
Preferably, the determination process of reticular density threshold value is in step S2, passes through same levels reticular density and mesh
Several relationship determines.
Preferably, reticular density is equal to the ratio of road total length degree and screening area in the Minimum Area comprising mesh.
Preferably, the determination process of road stroke connection importance threshold value is in step S2, can be divided by scheming upper vision
The minimum range distinguished and target proportion ruler determine.
Preferably, the division methods of road stroke type include following content in step S3,
S301, will be with road stroke (Si) head-end connect other roads stroke set be denoted as StartV (Si)；With
Road stroke (Si) other roads stroke collection for connecting of distal point is combined into EndV (Si)；Road stroke (Si) tip arc
Number of segment mesh is BurrN (Si)；With road strokeSiThe associated network meshes number of tip segmental arc be Net (Li)；
S302, road stroke is divided into following 4 class by 4 parameters more than judging,
I class road stroke:Net (Li)=0.
II class road stroke:intersection [StartV (Si),EndV(Si)] > 0 and BurrN (Si)=1 and Net
(Li)>0。
Group III road stroke:intersection [StartV (Si),EndV(Si)] > 0 and BurrN (Si) > 1 and Net
(Li)>0。
IV class road stroke:intersection [StartV (Si),EndV(Si)]=0 and Net (Li)>0。
Preferably, the classified order in step S8 is to be first the mesh containing class road stroke, followed by contain class
The mesh of road stroke is finally containing class road stroke mesh.
The beneficial effects of the present invention are: 1, can take into account path connected, integrality and road network network characterization and part it is close
Multiple features are spent to coordinate to complete road network selection.2, when carrying out the selection of large scale road, the space of road network can preferably be kept
Characteristic.3, when carrying out the selection of large scale road, the connectivity and integrality of road network can be preferably kept, and taking into account
While road network connectivity, the road network structure of road is summarised well.
Detailed description of the invention
Fig. 1 is the flow chart of road network choosing method in the embodiment of the present invention；
Fig. 2 is tip segmental arc and tip mesh schematic diagram in the embodiment of the present invention；
Fig. 3 is the estimation secondary road reticular density profiles versus of reticular density threshold value in the embodiment of the present invention；
Fig. 4 is the estimation main roads mesh Density Distribution comparison of reticular density threshold value in the embodiment of the present invention；
Fig. 5 is road stroke classification schematic diagram in the embodiment of the present invention；
Fig. 6 is ten thousand standard map sheet of 1:5 in the embodiment of the present invention；
Fig. 7 is that the road network in the embodiment of the present invention based on stroke chooses result；
Fig. 8 is that the road network in the embodiment of the present invention based on mesh chooses result；
Fig. 9 is the selection result that road network choosing method of the invention is used in the embodiment of the present invention.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with attached drawing, to the present invention into
Row is further described.It should be appreciated that the specific embodiments described herein are only used to explain the present invention, it is not used to
Limit the present invention.
As shown in Figure 1, the present invention provides the road network choosing methods for taking multiple features coordination under a kind of large scale into account, including
Following steps:
S1, point, segmental arc, Polygon Topology are constructed for road network, identifies mesh therein；Road semanteme, geometry are considered simultaneously
And topological characteristic generates stroke connection, and identifies tip segmental arc and tip mesh；
S2, reticular density threshold value and road stroke connection importance threshold value are determined；
S3, according to tip segmental arc and tip mesh, divide road stroke type；
S4, judge whether each stroke connection in ready-portioned road stroke type is containing tip mesh
Stroke connection, if it is not, thening follow the steps S5；If so, thening follow the steps S7.
S5, according to road stroke type, calculate the importance of road stroke connection；
S6, judge whether the importance of road stroke connection is less than stroke connection importance threshold value, if so, deleting
Road stroke connection, if it is not, then retaining road stroke connection；
S7, it the stroke connection containing tip mesh is collected obtains tip mesh set；
S8, classified according to the type containing road stroke in mesh to tip mesh set, handle the big of identification
In the tip mesh of reticular density threshold value, the maximum tip mesh of density and associated road stroke set are separated, and
Compare road stroke importance, obtains the smallest road stroke of importance；
S9, the smallest road stroke of importance is deleted；And judge whether that suspension segmental arc can be generated, if not generating suspension arc
Section, then delete road stroke, and merge the topological Polygon of road stroke the right and left, generate new mesh；If
Suspension segmental arc is generated, then deletes the tip section of road stroke in tip mesh, merges the topology of the section the right and left
Polygon generates new mesh；
S10, judge whether currently processed tip mesh is that the last one in tip mesh set is greater than reticular density threshold
The tip mesh of value, if so, the mesh that output is new, if it is not, then return step S8.
In the present embodiment, the suspension segmental arc is the radian that a part has connection, remainder connectionless.
In the present embodiment, by using the above method, make can to take into account during choosing road network path connected, complete
Whole property and road network network characterization and local density's multiple features are coordinated to complete road network selection.
Embodiment one
As shown in Fig. 2, the present embodiment is explained for step S1, road network choosing method of the invention needs while considering
Road semanteme, geometry and topological characteristic generate stroke connection, and carry out the identification of the tips features such as tip segmental arc, tip mesh.
In the present embodiment, stroke good continuity principle, the concept in Gestalt cognitive principles go out from unicursal
It is generated in the thought of curved section.Road network point, line, surface topology is constructed, and forms road according to information such as segmental arc semanteme, direction, length
Road stroke connection, such as the road stroke connection S in Fig. 21、S2、S3、S4、S5、S6.For tip segmental arc, if road stroke
A certain segmental arc in connection connect with road stroke in all segmental arcs intersection number less than 2, then the segmental arc is referred to as the road
Tip segmental arc in road stroke connection, tip segmental arc include S1In segmental arc AB, DE, S2In segmental arc FG, IJ, S3In arc
Section KL, NO, S4In segmental arc BG, LP, S5In segmental arc CH, MQ, S6In segmental arc DI, IN.Meanwhile for there are head and the tail nodes
Identical closure segmental arc, the closure segmental arc also belong to tip segmental arc.
In the present embodiment, for tip mesh, then according to road network topology relationship, identify network meshes, as mesh I, II,
III, IV, the mesh containing tip segmental arc in road stroke connection is known as tip mesh, such as mesh I, II, IV.
Embodiment two
As shown in Figure 3 and Figure 4, the present embodiment is explained for step S2, is needed in road network choosing method of the invention
It calculates and determines reticular density threshold value (TN) and two parameters of road stroke connection importance threshold value (TS), assist subsequent development road
The selection of road stroke.
In the present embodiment, whether the mesh in road is chosen, and is needed through network meshes density and reticular density threshold value
(TN) it is determined after being compared；Reticular density refers to the ratio of road total length degree and screening area in the Minimum Area comprising mesh
Value, such as following formula:
D=P/A
Wherein, D indicates reticular density, and P is section total length on mesh boundary, and A is the area of mesh.
In the present embodiment, reticular density threshold value (TN) can usually be determined using the method based on statistical analysis, by dividing
The relationship of the comprehensive front and back same levels reticular density of master drawing and mesh number is analysed to determine density threshold.Source scale bar 1:1 ten thousand, mesh
Illustrate for mark scale bar 1:5 ten thousand, road is divided into main roads and two kinds of secondary road, then mesh is divided by main roads structure
At mesh and the mesh that is made of secondary road.Curve indicates density value in Fig. 3 and Fig. 4 and density is the mesh number of the value
Relationship respectively indicates the Density Distribution comparison under two class mesh different scales.Fig. 3 can be seen that density value 0.012m/m is two
The line of demarcation in section, mesh of the density greater than 0.012 need to choose under 1: 5 ten thousand scale bar；The distribution curve of Fig. 4 is it is found that two
Kind of main roads mesh Density Distribution is almost coincide, show main roads under 1: 5 ten thousand scale bar almost without giving up, then can be with
0.012 is chosen as mesh density threshold (TN) under 1: 5 ten thousand scale bar.
In the present embodiment, whether the stroke in road is chosen, and is needed through road stroke importance and road
Stroke connection importance threshold value (TS) determines after being compared；Wherein road stroke importance is for containing tip mesh
Road stroke is different with the road stroke calculation method without containing tip mesh.For the road containing tip mesh
Stroke calculates stroke importance according to the following formula:
I=BC × L
Wherein, I is stroke importance；BC is stroke Betweenness Centrality；L is stroke length.
For not containing the road stroke of tip mesh, stroke importance is calculated according to the following formula.
I=(1+N) × L
Wherein, I is stroke importance；N is stroke degree of communication；L is stroke length.
Road stroke connection importance threshold value (TS) is by scheming the upper distinguishable minimum range of vision and target proportion ruler
To determine.In general, cartographic expert thinks on figure that the distinguishable distance of vision is 0.4mm, then target proportion ruler (1:Scaletarget)
Under, road stroke connection importance threshold value (TS) calculates according to the following formula:
Ts=0.4 × Scaletarget
Embodiment three
As shown in figure 5, the road network choosing method in the present invention is needed according to stroke first and last associations in the present embodiment
Road stroke set, the number of tip segmental arc and tip mesh number divide road stroke type.It will be with road stroke
(Si) head-end connect other roads stroke set be denoted as StartV (Si)；With road stroke (Si) distal point connects
Other roads stroke collection is combined into EndV (Si)；Road stroke (Si) tip segmental arc number be BurrN (Si)；With road
stroke(Si) the associated network meshes number of tip segmental arc be Net (Li)；
S302, road stroke is divided into following 4 class by 4 parameters more than judging,
I class road stroke:Net (Li)=0.
II class road stroke:intersection [StartV (Si),EndV(Si)] > 0 and BurrN (Si)=1 and Net
(Li)>0。
Group III road stroke:intersection [StartV (Si),EndV(Si)] > 0 and BurrN (Si) > 1 and Net
(Li)>0。
IV class road stroke:intersection [StartV (Si),EndV(Si)]=0 and Net (Li)>0.Such as Fig. 5 institute
Show, I class road stroke has S1、S2、S3、S4、S9、S11、S12、S13、S14、S15, II class road stroke has S8, Group III road
Stroke has S5, IV class road stroke has S6、S7、S10。
Example IV
As shown in Fig. 6 to 9, road selection is carried out using three kinds of methods in the present embodiment, wherein Fig. 6 is ten thousand standard drawing of 1:5
Width, Fig. 7, Fig. 8 and Fig. 9 are using the road network choosing method based on stroke, the road network choosing method based on mesh and sheet respectively
Inventive method, road chooses result when from the synthesis of 1:1 ten thousand to 1:5 ten thousand.It is compared with Fig. 6 standard map sheet result, for rectangle A
Interior road, the road network choosing method based on stroke is as a result, remain the section a of end, but be lost connection and made in Fig. 7
Section b, causes path connected to be destroyed；Road network choosing method based on mesh is as a result, retain section b, but in Fig. 8
It is lost section a, road integrality is caused to be destroyed；Choosing method of the present invention remains section a, b simultaneously in Fig. 9, thus
The connectivity and integrality of road network are preferably kept.In addition, the road in rectangle B is influenced by mesh aggregation, is based on
The road network choosing method of stroke can not detect the labyrinth at this in Fig. 7, original structure is caused to be lost, and suspension arc occur
Section；Road network choosing method based on mesh, though accounting for the connectivity of road network at this in Fig. 8, significant change occurs for structure；This
Invention choosing method is then extracted trunk roads herein in Fig. 9 well, general well while taking road network connectivity into account
The road network structure at this is included.
By using above-mentioned technical proposal disclosed by the invention, following beneficial effect has been obtained:
The present invention provides the road network choosing methods for taking multiple features coordination under a kind of large scale into account, by using the method
To the progress of falling library road network selection, path connected, integrality and road network network characterization can be taken into account and local density's multiple features are assisted
It adjusts and completes road network selection；When carrying out the selection of large scale road, the spatial character of road network can be preferably kept；It is carrying out greatly
When scale bar road is chosen, the connectivity and integrality of road network can be preferably kept, and taking the same of road network connectivity into account
When, the road network structure of road is summarised well.
The above is only a preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications are also answered
Depending on protection scope of the present invention.
Claims (8)
1. taking the road network choosing method of multiple features coordination under a kind of large scale into account, it is characterised in that: include the following steps,
S1, point, segmental arc, Polygon Topology are constructed for road network, identifies mesh therein；Semantic road, geometry are considered simultaneously and are opened up
It flutters feature and generates stroke connection, and identify tip segmental arc and tip mesh；
S2, reticular density threshold value and road stroke connection importance threshold value are determined；
S3, according to tip segmental arc and tip mesh, divide road stroke type；
S4, judge whether each stroke connection in ready-portioned road stroke type is that the stroke containing tip mesh connects
It connects, if it is not, thening follow the steps S5；If so, thening follow the steps S7.
S5, according to road stroke type, calculate the importance of road stroke connection；
S6, judge whether the importance of road stroke connection is less than stroke connection importance threshold value, if so, deleting the road
Road stroke connection, if it is not, then retaining road stroke connection；
S7, it the stroke connection containing tip mesh is collected obtains tip mesh set；
S8, classified according to the type containing road stroke in mesh to tip mesh set, handle identification is greater than net
The tip mesh of eye density threshold separates the maximum tip mesh of density and associated road stroke set, and compares
Road stroke importance obtains the smallest road stroke of importance；
S9, the smallest road stroke of importance is deleted；And judge whether that suspension segmental arc can be generated, if not generating suspension segmental arc,
Road stroke is then deleted, and merges the topological Polygon of road stroke the right and left, generates new mesh, and execute
S10；If generating suspension segmental arc, the tip section of road stroke in tip mesh is deleted, the section the right and left is merged
Topological Polygon, generate new mesh, and execute S10；
S10, judge whether currently processed tip mesh is that the last one in tip mesh set is greater than reticular density threshold value
Tip mesh, if so, the mesh that output is new, if it is not, then return step S8.
2. taking the road network choosing method of multiple features coordination under large scale according to claim 1 into account, it is characterised in that: step
The identification process of tip segmental arc is to identify all segmental arcs in connecting in road stroke connection with road stroke in rapid S1
Segmental arc of the intersection number less than 2, the segmental arc are referred to as the tip segmental arc in road stroke connection；It identifies and is tied in the presence of head and the tail simultaneously
The identical closure segmental arc of point, the closure segmental arc also belong to tip segmental arc.
3. taking the road network choosing method of multiple features coordination under large scale according to claim 1 into account, it is characterised in that: step
The identification process of tip mesh is in rapid S1, according to road network topology relationship, identifies network meshes, will contain road stroke connection
The mesh of middle tip segmental arc is known as tip mesh.
4. taking the road network choosing method of multiple features coordination under large scale according to claim 1 into account, it is characterised in that: step
The determination process of reticular density threshold value is in rapid S2, is determined by the relationship of same levels reticular density and mesh number.
5. taking the road network choosing method of multiple features coordination under large scale according to claim 4 into account, it is characterised in that: net
Eye density is equal to the ratio of road total length degree and screening area in the Minimum Area comprising mesh.
6. taking the road network choosing method of multiple features coordination under large scale according to claim 1 into account, it is characterised in that: step
The determination process of road stroke connection importance threshold value is in rapid S2, by scheming the upper distinguishable minimum range of vision and target
Scale bar determines.
7. taking the road network choosing method of multiple features coordination under large scale according to claim 1 into account, it is characterised in that: step
The division methods of road stroke type include following content in rapid S3,
S301, will be with road stroke (Si) head-end connect other roads stroke set be denoted as StartV (Si)；With road
stroke(Si) other roads stroke collection for connecting of distal point is combined into EndV (Si)；Road stroke (Si) tip segmental arc number
Mesh is BurrN (Si)；With road strokeSiThe associated network meshes number of tip segmental arc be Net (Li)；
S302, road stroke is divided into following 4 class by 4 parameters more than judging,
I class road stroke:Net (Li)=0.
II class road stroke:intersection [StartV (Si),EndV(Si)] > 0 and BurrN (Si)=1 and Net (Li)>
0。
Group III road stroke:intersection [StartV (Si),EndV(Si)] > 0 and BurrN (Si) > 1 and Net (Li)>
0。
IV class road stroke:intersection [StartV (Si),EndV(Si)]=0 and Net (Li)>0。
8. taking the road network choosing method of multiple features coordination under large scale according to claim 1 into account, it is characterised in that: step
Classified order in rapid S8 be first the mesh containing class road stroke, the followed by mesh containing class road stroke,
It is finally containing class road stroke mesh.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111611668A (en) * | 2020-06-06 | 2020-09-01 | 兰州交通大学 | Road network automatic selection method considering geometric features and semantic information |
| CN112035592A (en) * | 2020-09-07 | 2020-12-04 | 中国测绘科学研究院 | Road network isolated mesh elimination method based on stroke tip characteristics |
| CN112052549A (en) * | 2020-09-09 | 2020-12-08 | 中国测绘科学研究院 | Method for selecting roads in small mesh gathering area |
| CN113393129A (en) * | 2021-06-17 | 2021-09-14 | 中国测绘科学研究院 | Massive building multi-scale block combination method considering road network association constraint |
| CN116071455A (en) * | 2023-01-29 | 2023-05-05 | 兰州交通大学 | Road network stroke generation method based on same-scale similarity relation |
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| CN111611668A (en) * | 2020-06-06 | 2020-09-01 | 兰州交通大学 | Road network automatic selection method considering geometric features and semantic information |
| CN112035592A (en) * | 2020-09-07 | 2020-12-04 | 中国测绘科学研究院 | Road network isolated mesh elimination method based on stroke tip characteristics |
| CN112052549A (en) * | 2020-09-09 | 2020-12-08 | 中国测绘科学研究院 | Method for selecting roads in small mesh gathering area |
| CN112052549B (en) * | 2020-09-09 | 2021-03-05 | 中国测绘科学研究院 | Method for selecting roads in small mesh gathering area |
| CN113393129A (en) * | 2021-06-17 | 2021-09-14 | 中国测绘科学研究院 | Massive building multi-scale block combination method considering road network association constraint |
| CN113393129B (en) * | 2021-06-17 | 2022-04-19 | 中国测绘科学研究院 | Massive building multi-scale block combination method considering road network association constraint |
| CN116071455A (en) * | 2023-01-29 | 2023-05-05 | 兰州交通大学 | Road network stroke generation method based on same-scale similarity relation |
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